1. Field of the Invention
The present invention relates to a predictive control method and apparatus for predicting a controlled variable upon the control of an object; to be nonlinearly controlled, such as a manipulator.
2. Description of the Related Art
As a method for controlling an object to be nonlinearly controlled, such as a manipulator, two methods are conventionally known: a nonlinear compensation/ feedback control-combined method and a method of computed torque (or inverse problem method) for finding a manipulated variable from a mathematical model of an object. These respective methods cannot make accurate control of an object if the mathematical model (the dynamic characteristic of the mathematical model) is not known.
In addition to the aforementioned methods, several object control methods using a controllable neural network have been proposed which comprise enabling the neural network to acquire the dynamic characteristic of an object through the learning by the neural network and enabling the characteristic to be controlled even if an associated mathematical model is unknown. However, the method comprises performing feed-forward control by computing a manipulated variable from a target controlled variable so that no compensation can be made for any disturbance involved.
The present invention is directed to a predictive control method and apparatus for controlling an object for predictive evaluation, which can control an object unknown in mathematical model for its dynamic characteristic in a predictive evaluation fashion and can compensate for any disturbance involved.